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Let Claude Code read, edit, and run Jupyter notebooks efficiently.
This MCP tool appears to be an open-source Jupyter notebook interaction server with no required secrets and no declared remote endpoints, with no obvious high-risk red flags in the provided materials. However, it is objectively capable of local code execution, and notebook interaction typically involves local files and kernel operations, so it should be used with normal caution.
The materials state that no keys or environment variables are required, and no API tokens, account credentials, or third-party authentication requirements are disclosed, so credential exposure appears limited.
No remote endpoints or external service connections are declared, and based on the provided materials there is no factual indication of user data being sent to external networks.
The objective checks mark it as executes-code, and its stated purpose is Jupyter notebook interaction, which typically implies invoking local notebook/kernel code execution or related processes; this is a normal high-privilege capability for this tool class and warrants controlled use.
As a notebook interaction tool, it would typically need to read, create, or modify local notebooks and related data files; the materials do not show permissions beyond its stated function, but local data access should be assumed.
The project is open source under the MIT License and is in principle auditable, which is a meaningful risk-reducing factor; however, it comes from a third-party registry, has 0 stars, and an unknown maintenance status, so its maturity and ongoing upkeep remain worth watching.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Claude Code Notebook MCP" yet — see the docs or source repo.
Connect to the Jupyter notebook in the current project, find the cell causing the execution error, analyze the cause, modify the code directly, rerun the relevant cells, and summarize the fix.
Returns the failing cell, corrected code, execution results, and an explanation of the issue.
Open this notebook, read its data-processing context, and complete the missing exploratory analysis cells, including descriptive statistics, missing-value checks, and visualizations, while keeping the existing style consistent.
Generates and inserts new analysis cells with statistics, charts, and a well-structured notebook.
Review this Jupyter notebook’s execution order, variable dependencies, and duplicated code, then refactor it into a version that runs cleanly from top to bottom and add necessary explanatory Markdown.
Produces a cleaner, reproducible notebook with correct execution order and explanatory documentation.
Control Google NotebookLM end-to-end for research, notes, chat, and exports.
Make project docs instantly accessible so Claude Code understands architecture and conventions.
Enable Claude Code to perform coding tasks through the OpenAI Codex CLI.
Create, organize, and manage notes in Claude Desktop through MCP tools.
Load, edit, search, and save Jupyter notebooks through MCP tools.
Query Claude Code transcript analytics for cost, safety, audit, and efficiency insights.